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/technical-to-business-translator

@e4e97c5

Translate technical analysis into business language. Use when explaining statistical concepts to non-analysts, simplifying technical findings, or bridging communication between data teams and business stakeholders.

Use this Skill: https://skilld.dev/gh/nimrodfisher/data-analytics-skills/technical-to-business-translator

This session only. Nothing lands on disk.

assetstranslation_template.md

≈456 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Translation: [Analysis Title]

Original author: [name]
Translator: [name]
Target audience: [persona — Executive / PM / Finance / Operations / Marketing]
Date: [YYYY-MM-DD]


Business Version (for the target audience)

Key Finding

[The headline result in one plain-language sentence. No jargon.]

What This Means

[2–3 sentences expanding on the finding in business terms. Answer "so what?" explicitly.]

What We Recommend

[One concrete recommended action. Include who should take it and by when.]

How Confident Are We

[One sentence on confidence. Example: "We're highly confident in this finding — it's based on 3 months of data from 12,000 customers." Or: "This is an early signal — we'd recommend validating with a formal experiment before acting at scale."]

Key Caveat

[One limitation, stated plainly. Example: "This doesn't account for customers acquired before 2022, so the pattern may differ for the older cohort."]


Jargon Replacements Applied

Original term Replaced with
[e.g. p-value < 0.05] [e.g. "We're 95% confident the difference is real"]
[e.g. AUC = 0.83] [e.g. "The model correctly identifies at-risk customers 83% of the time"]

Readability

Metric Before After Target
FK Grade Level [X] [Y] ≤ 10 (executive) / ≤ 12 (business)
Avg words/sentence [X] [Y] ≤ 18
Jargon terms flagged [X] [Y] 0

Original Technical Version (for peer reviewers)

[Paste the original technical text here — or link to it. Keep it visible so technical reviewers can verify the translation didn't distort the finding.]


Translation checked against references/translation_pattern_library.md and references/stakeholder_personas.md.

Source: SKILL.md on GitHub

No alerts16d4 checks · Risk SAFE
  • Gen Agent Trust Hub16d

    This skill provides templates, scripts, and libraries to translate technical analysis and data science jargon into business language for non-technical stakeholders. It includes an automated jargon detector and readability scorer, both implemented securely in Python without any unsafe third-party dependencies, external network calls, or dangerous command execution.

  • Socket16d

    No alerts

  • Snyk16d

    Risk: LOW · No issues

  • ZeroLeaks5mo

    Score: 93/100 · 2 sections analyzed

Signed by skilld at e4e97c5. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 5 days ago.

Activeupdated 5 months ago

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